📖 Biomedical knowledge mining using GOSemSim and clusterProfiler
Multi-Enrichment Analysis of Gene Set Enrichment Analysis Results
TUCCA's RNA-Seq Workflow for Read Quantification, Differential Expression, and Pathway Enrichment Analysis
Working Demo on GO Enrichment Analysis using topGO, clusterProfiler and Enrichr/enrichR. Visit repo website for HTML output
Deposited R scripts allow to execute a complete RNA-seq Pipeline, starting from sequence reads (FASTQ files) to mapping/annotate the genome using a reference, to counts the number of reads for every gene. when raw counts are obtained, DESeq2 module permits to find differentially expressed genes (DEG) and to perform statistical analysis. The last…
Context-aware restriction of the Gene Ontology (GO) for enrichment analysis.
Bulk RNA-seq analysis of colorectal cancer (GSE50760): QC, differential expression (limma), and GO/KEGG/GSEA enrichment in R
Bayesian network plot for the enrichment analysis results
Single-cell RNA-seq analysis — Pandey et al. 2022
End-to-end RNA-seq pipeline on TCGA-BRCA (213 samples): DESeq2 differential expression, clusterProfiler functional enrichment, and ML-based biomarker ranking (Random Forest, LASSO, SVM) achieving >96% classification accuracy
GSApp Pathway Analysis
Singularity container for running gene ontology anlaysis
This repository contains an end-to-end RNA-Seq DGE Analysis pipeline built in RStudio to analyze host transcriptional responses to SARS-CoV-2 across multiple cell lines. Using raw read counts from the GSE147507 benchmark study, this pipeline handles complex multi-condition experimental matrices and implements rigorous quality-control protocols.
Reproduction of the human glioma single-cell atlas (GSE138794): Seurat + Harmony + clusterProfiler
An investment advisory firm needs to segment stock offerings so they may offer their customers understandable investment options.
Differential gene expression and GSEA analysis of nasal swab RNA-seq data comparing SARS-CoV-2 infection vs no-virus samples, using the limma-voom pipeline and clusterProfiler.
Este projeto teste, analisa perfis de expressão gênica de dados de RNA-Seq para identificar genes diferencialmente expressos em pacientes com Doença Arterial Coronariana (DAC) usando R.
Differential gene expression and GSEA analysis of RNA-seq data from COVID-19 patient lung tissue vs healthy control donors, using DESeq2 and clusterProfiler.
Comprehensive R bioinformatics container — single-cell, bulk RNA-seq, methylation, ATAC-seq, and pathway analysis (2026)
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